At present, a graphics processing unit (GPU) is advanced to be capable of processing a giga-level, i.e., processing gigabits of drawing commands per second. The trends of computer graphics are toward larger resolution images (e.g., 4K by 4K) and complex rendering. However, for some computation platforms (e.g., handheld devices), having powerful computation capabilities (accompanying with great power consumption) and large bandwidth is not realistic. A tiling engine may be equipped in the GPU of a handheld electronic device, and divide an image into a plurality of tiles. A tile-based rendering architecture can contribute to utilizing and accessing a local memory, and the usage of the bandwidth can be more efficiently.
How to reduce the transmission the bandwidth between the GPU and the system, and/or save the computation of a graphics rendering pipeline in the GPU is a subject in the field. In some current techniques, an Adaptive Scalable Texture Compress (ASTC) and a Transaction Elimination techniques are utilized to reduce the bandwidth between the GPU and the system, and achieve the reduction of power consumption. ASTC is a compress technique utilizing illumination of texture color. The “Transaction Elimination” technique can be utilized to compare rendered pixels in a current frame with rendered pixels located at the same positions in a previous frame, and save the bandwidth. In the current techniques, the transaction elimination is performed after the pixels are rendered, i.e., after a stage of rasterization is finished. Namely, the transaction elimination has to be performed on the pixels after the rendering computation. Therefore, the effect of saving the computation in the graphics rendering pipeline of the current techniques is limited.